‘Data Silos’ & ‘Information Islands’

‘Data Silos’ and ‘Information Islands’ lead to a distorted version of the truth

Most Manufacturing businesses have a multitude of different systems generating Engineering data every day.

These applications are tremendously useful to the departments that use them, and those departments use the data they produce as the foundation for decision-making and goal-setting activities.

Rarely, though, do those systems talk to each other. Individual information systems handle their own data, rather than drawing from a common data source, a ‘data silo’.

They may be connected through a series of file exports and imports, but they aren’t working from the same pool of information. Instead, each of these systems is hoarding its data and putting roadblocks in the way of true data transparency.

Perhaps key performance indicators are exported to a spreadsheet and shared through emails–or worse, bad photocopies–and is then manually manipulated so it can then be imported into some other system that desperately needs the information, but the data in those situations still exists as a multitude, not a singularity, and a massive amount of manual labour is required to make the data usable anywhere else — which coincidentally makes it unusable by the very system that generated it in the first place.

Manual data manipulation is not your friend. Any time you have to start renaming rows and columns and cleaning up discrepancies before bringing your data over to a different system, you’re introducing not only delays in the timeliness of the data, but a huge potential for inadvertent errors and multiple versions of the truth. And even if you’ve managed to get a workable system of data sharing going on, the simple truth is that you’ve got a system rife with ‘data silos’and ‘information Islands’ and your data will never be integrated enough for truly significant, timely, and robust analysis.

Data silos are usually an accident brought about when different departments implement various information systems that meet their specific needs. To them, the system they’ve chosen to use is everything they’ve ever wanted, but that may not be true to the corporation as a whole.

More critically, while these individual systems may provide robust analysis within their own domain, they may miss interesting relationships between seemingly unrelated data points. And because there is inevitably a human gatekeeper determining which key performance indicators are worth exporting and which ones are not, a significant amount of data is simply discarded as not relevant to the discussion at hand, even if it might hold the key to an interesting little relationship that leads to better profitability.

When you start working with truly integrated data, pulling information from across your entire organization and feeding it into a tool that lets you see the big picture or narrow your scope to information specific to individual business processes, everyone wins, from the top to the bottom of your organisation.

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